TILES S3B2-ML:
Summer School on Sensor-Based Behavioral Machine Learning


© Pedro Szekely (Flickr, 2010)

What: Analyzing Bio-behavioral Data to Model Human Behavior (Course code: S3B2-ML)

When: August 3rd-4th, 2020

Due to the ongoing uncertainty with COVID-19, we are changing the summer school to a live webinar that all students can attend for free.

Talks will be available on YouTube/SigPort

Various human conditions, such as stress and depression, are both common and are detrimental to our psyche and body. Finding those most at risk, however, can be exceedingly costly without methods to automatically detect high-risk individuals. We are inviting students to a summer school, where they will analyze multimodal bio-behavioral data, such FitBit sensors, to infer and better understand human behaviors. This critical task blends several fields from psychology to signal processing to AI, which are not often studied together. We have invited several experts from diverse fields to how discuss how sensors, data extraction, and machine learning can combine to create critical behavior sensing tools. Students will take knowledge gleaned from these experts to create and tackle projects with real human sensor data. We hope for graduate students and postdocs to see the webinar.

Important Dates

Date Description
May 1st Application deadline [extended] (due by 23:59 PDT)
All students welcome
June 1st Notification of acceptance
July 15th Registration deadline
August 3rd School starts

Speakers

Theodora Chaspari

Assistant Professor, Department of Computer Science & Engineering
Texas A&M University

Anind K.Dey

Dean and Professor
University of Washington

Tiago H. Falk

Associate Professor
Institut National de la Recherche Scientifique (INRS)

Luca Foschini

Co-founder & Chief Data Scientist
Evidation Health, Inc.

Kristina Lerman

Project Leader & Research Associate Professor
Information Sciences Institute, USC

Stephen M. Mattingly

Postdoctoral Researcher, Department of Computer Science and Engineering
University of Notre Dame

Jyoti Mishra

Assistant Professor, Psychiatry
UC San Diego

Akane Sano

Assistant Professor, Electrical and Computer Engineering
Rice University

Björn W. Schuller

Full Professor & Head of the Chair of Embedded Intelligence for Health Care and Wellbeing
University of Augsburg

Donna Spruijt-Metz

Director USC-CESR Mobile and Connected Health Program
University of Southern California, Dornsife

Clemens Stachl

Postdoctoral Researcher, Media and Personality Lab
Stanford University

Organizers

Keith Burghardt

Computer Scientist
USC Information Sciences Institute

Benjamin Girault

Postdoctoral Scholar
Unversity of Southern California

Kristina Lerman

Project Leader and Research Associate Professor
Information Sciences Institute, Unversity of Southern California

Emilio Ferrara

Research Team Leader and Assistant Research Professor
Information Sciences Institute, Unversity of Southern California

Shrikanth Narayanan

Niki and C. L. Max Nikias Chair in Engineering
Unversity of Southern California

Schedule

Students will be learning about the various areas of AI applicable to converting sensor data into viable predictions of human stress, performance, personality, and other psychological factors. Moreover, they will learn about signal processing, embedding, and other ways in which raw data can be converted into useful features.

Time of Day August 3rd August 4rd
08:50 PST [Keith Burghardt (Opening remarks)]
09:00 PST Akane Sano Clemens Stachl
09:45 PST Luca Foschini Stephen Mattingly
10:30 PST Jyoti Mishra Donna Spruijt-Metz
11:15 PST Björn Schuller Anind Dey
12:00 PST Theodora Chaspari TILES data collection
12:45 PST Tiago Falk TILES modeling
13:30 PST [Keith Burghardt / Benjamin Girault (Closing remarks)]

Registration

Deadline: July 15th (23:59 PDT)

Click here to register

The school is open to everyone interested who interested in how bio-behavioral data, whether they want to analyze data from wearable sensors like FitBit, or model how sensor data correlates with personality traits, stress, and sleep. Students with machine learning background are encouraged to apply, as well as those who have worked on modeling human behavior. The aim of this summer school and workshop is to bring a broad group of researchers interested in how health can be passively tracked to improve livelihoods.

Cost

Registration will be free.

Get in touch

4676 Admiralty Way
Suite #1001
Marina del Rey, California USA 90045


TILESsummerschool@isi.edu


(310) 448-9433